Young Men s Sexual Behaviour in Finland and Estonia : Opportunities for prevention of sexually transmitted infections

Background: The incidence of sexually transmitted infections (STIs) in most EU states has gradually increased and the rate of newly diagnosed HIV cases has doubled since 1999. STIs differ in their clinical features, prognosis and transmission dynamics, though they do share a common factor in their mode of transmission −that is, human behaviour. The evolvement of STI epidemiology involves a joint action of biological, epidemiological and societal factors. Of the more immediate factors, besides timely diagnosis and appropriate treatment, STI incidence is influenced by population patterns of sexual risk behaviour, particularly the number of sexual partners and the frequency of unprotected intercourse. Assessment of sexual behaviour, its sociodemographic determinants and time-trends are important in understanding the distribution and dynamic of STI epidemiology. Additionally, in the light of the basic structural determinants, such as increased level of migration, changes in gender dynamics and impacts from globalization, with its increasing alignment of values and beliefs, can reveal future challenges related to STI epidemiology. STI case surveillance together with surveillance on sexual behaviour can guide the identification of preventive strategies, assess their effectiveness and predict emerging trends. The objective of this study was to provide base line data on sexual risk behaviour, self-reported STIs and their patterns by sociodemographic factors as well as associations of sexual risk behaviour with substance use among young men in Finland and Estonia. In Finland national population based data on adult men s sexual behaviour is limited. The findings are discussed in the context of STI epidemiology as well as their possible implications for public health policies and prevention strategies. Materials and Methods: Data from three different cross-sectional population-based surveys conducted in Finland and Estonia, during 1998 2005, were used. Sexual behaviour- and health-related questions were incorporated in two surveys in Finland; the Health 2000, a large scale general health survey, focussed on young adults, and the Military health behavioural survey on military conscripts participating in the mandatory military training. Through research collaboration with Estonia, similar questions to the Finnish surveys were introduced to the second Estonian HIV/AIDS survey, which was targeted at young adults. All surveys applied mail-returned, anonymous, self-administered questionnaires with multiple choice formatted answers. Results: In Finland, differences in sexual behaviour between young men and women were minor. An age-stratified analysis revealed that the sex-related difference observed in the youngest age group (18 19 years) levelled off in the age group 20 24 and almost disappeared among those aged 25 29. Marital status was the most important sociodemographic correlate for sexual behaviour for both sexes, singles reporting higher numbers of lifetime-partners and condom use. This effect was stronger for women than for men. However, of those who had sex with casual partners, 15% were married or co-habiting, with no difference between male and female respondents. According to the Military health behavioural survey, young men s sexual risk behaviour in Finland did not markedly change over a period of time between 1998 and 2005. Approximately 30−40% of young men had had multiple sex partners (more than five) in their lifetime, over 20% reported having had multiple sex partners (at least three) over the past year and 50% did not use a condom in their last sexual intercourse. Some 10% of men reported accumulation of risk factors, i.e. having had both, multiple sex partners and not used a condom in their last intercourse, over the past year of the survey. When differences and similarities were viewed within Finland and Estonia, a clear sociodemographic patterning of sexual risk behaviour and self-reported STIs was found in Finland, but a somewhat less consistent trend in Estonia. Generally, both, alcohol and drug use were strong correlates for sexual risk behaviour and self-reported STIs in Finland and Estonia, having a greater effect on engagement with multiple sex partners rather than unprotected intercourse or self-reported STIs. In Finland alcohol use, relative to drug use, was a stronger predictor of sexual risk behaviour and self-reported STIs, while in Estonia drug use predicted sexual risk behaviour and self-reported STIs stronger than alcohol use. Conclusions: The study results point to the importance for prevention of sexual risk behaviour, particularly strategies that integrate sexual risk with alcohol and drug use risks. The results point to the need to focus further research on sexual behaviour and STIs among young people; on tracking trends among general population as well as applying in-depth research to identify and learn from vulnerable and high-risk population groups for STIs who are exposed to a combination of risk factors.

Trends and Explanations for Socioeconomic Differences in Physical Activity

Very limited scientific knowledge exists on the trends and explanations of socioeconomic differences in physical activity among adults. There is a paucity of studies examining whether determinants vary across socioeconomic position and different life stages. This study examines a) how socioeconomic differences in leisure-time and commuting physical activity have changed in Finland from 1978 to 2002 and b) the contribution of childhood socioeconomic position, adolescence sports and exercise, adulthood socioeconomic position, working conditions and other adulthood health behaviours to socioeconomic differences in leisure-time physical activity. This study utilised three population-based datasets collected by the National Institute for Health and Welfare (THL, formerly National Institute for Public Health): the Health Behaviour and Health among the Finnish Adult Population Study from 1978 to 2002 (N=96 105), the National FINRISK Study 2002 and its physical activity sub-study (N= 9 179), and the Health 2000 Study (N=8 028). Survey information was collected by self-administered questionnaires, interviews at home, and measurements made at the study site. The response rates varied from 69 to 89 per cent. Several socioeconomic measures were linked from the national population registers. Based on the results, those with low income were physically inactive during leisure-time and while commuting from 1978 to 2002. Manual worker women, however, were more physically active commuters compared to their counterparts. Parental socioeconomic position contributed directly to adulthood educational differences in leisure-time physical inactivity but also indirectly through adulthood socioeconomic position (occupation, household income) and other unhealthy behaviours (mainly smoking). Among those with low education participation in competitive sports in youth and among those with high education exercise in late adolescence contributed to leisure-time physical activity in adulthood. Long exposure to physically strenuous working conditions in men and current job strain in women contributed to occupational class differences in leisure-time physical activity. Socioeconomic differences in physical activity have remained similar for twenty years in Finland. Educational career seems to have a strong contribution to physical activity. To adopt a lifelong physically active life-style, one should participate in a range of different sports and exercise in adolescence and in youth, have a low exposure to physically and mentally strenuous working conditions in later life and have other healthy behaviours in later life.

Improving GPS time series for geodynamic studies

Accurate and stable time series of geodetic parameters can be used to help in understanding the dynamic Earth and its response to global change. The Global Positioning System, GPS, has proven to be invaluable in modern geodynamic studies. In Fennoscandia the first GPS networks were set up in 1993. These networks form the basis of the national reference frames in the area, but they also provide long and important time series for crustal deformation studies. These time series can be used, for example, to better constrain the ice history of the last ice age and the Earth s structure, via existing glacial isostatic adjustment models. To improve the accuracy and stability of the GPS time series, the possible nuisance parameters and error sources need to be minimized. We have analysed GPS time series to study two phenomena. First, we study the refraction in the neutral atmosphere of the GPS signal, and, second, we study the surface loading of the crust by environmental factors, namely the non-tidal Baltic Sea, atmospheric load and varying continental water reservoirs. We studied the atmospheric effects on the GPS time series by comparing the standard method to slant delays derived from a regional numerical weather model. We have presented a method for correcting the atmospheric delays at the observational level. The results show that both standard atmosphere modelling and the atmospheric delays derived from a numerical weather model by ray-tracing provide a stable solution. The advantage of the latter is that the number of unknowns used in the computation decreases and thus, the computation may become faster and more robust. The computation can also be done with any processing software that allows the atmospheric correction to be turned off. The crustal deformation due to loading was computed by convolving Green s functions with surface load data, that is to say, global hydrology models, global numerical weather models and a local model for the Baltic Sea. The result was that the loading factors can be seen in the GPS coordinate time series. Reducing the computed deformation from the vertical time series of GPS coordinates reduces the scatter of the time series; however, the long term trends are not influenced. We show that global hydrology models and the local sea surface can explain up to 30% of the GPS time series variation. On the other hand atmospheric loading admittance in the GPS time series is low, and different hydrological surface load models could not be validated in the present study. In order to be used for GPS corrections in the future, both atmospheric loading and hydrological models need further analysis and improvements.